Journal Articles
| Article Title | Authors | Abstract | ||||||
|---|---|---|---|---|---|---|---|---|
| PETS: A Pharmacological Effects of Targets Simulator towards Quantitative Evaluation of Drug Repositioning Candidates | Thanh Nguyen, Sara Ibrahim, and Jake Y. Chen*. | Under preparation | ||||||
| A Novel in vivo Model of Glioblastoma Radiation Resistance Identifies Long Non-coding RNAs and Targetable Kinases | Christian T. Stackhouse, Joshua C. Anderson, Zongliang Yue, Thanh Nguyen, Nicholas J. Eustace, Lara Ianov, Catherine P. Langford, Jelai Wang, James R. Rowland III, Chuan Xing, Fady M. Mikhail, Eddy S. Yang, Anita B. Hjelmeland, C. Ryan Miller, Jake Y. Chen, G. Yancey Gillespie, Christopher D. Willey | Submitted | ||||||
| A Commensurate Feature Selection Method in Data Preprocessing for Classification | IEEE Transactions on Knowledge and Data Engineering | Nuo Xu, Xuan Huang, Thanh Nguyen, and Jake Y. Chen* | Under Revision | |||||
| STAT3 signaling contributes to cellular metabolism changes of drug-persistent leukemic stem cells | Leukemia | Sweta B. Patel, Travis Nemkov, Davide Stefanoni, Gloria A. Benavides, Brittany L. Crown, Victoria R. Matkins, Virginia Camacho, Ashley T. Hoang, Danielle E. Tenen, Samuel L. Wolock, Jihye Park, Mahmoud A. Bassal, Li Ying, Zongliang Yue, Jake Y. Chen, Henry Yang, Daniel G. Tenen, Paul Brent Ferrell, Rui Lu, Victor Darley-Usmar, Angelo D’Alessandro, Ravi Bhatia, Robert S. Welner | Under Revision | |||||
| High Dimensional Analysis Reveals IL-4R as a Protective Factor to Prevent DN2 B-cell Development in SLE | J. Immunology | Min Gao, Shanrun Liu, Qi Wu, PingAr Yang, Alex Essman, Bao Luo, Oluwagbemiga A. Ojo, David Crossman, Michael R. Crowley, Ignacio Sanz, Jake Y. Chen, W. Winn Chatham, John D. Mountz*, and Hui-Chen Hsu*. | IF = 4.34 | Under Revision | ||||
| Vitamin D and Lumisterol Derivatives Can Act on Liver X Receptors (LXRs) | Scientific Reports | Andrzej T Slominski, Tae-Kang Kim, Shariq Qayyum, Yuwei Song, Zorica Janjetovic, Allen SW Oak, Radomir M Slominski, Chander Raman, Joanna Stefan, Carlos A Mier-Aguilar, Venkatram Atigadda, David K Crossman, Andriy Golub, Yaroslav Bilokin, Edith K Y Tang, Jake Y. Chen, Robert C Tuckey, Anton M Jetten, Yuhua Song | The interactions of derivatives of lumisterol (L3) and vitamin D3 (D3) with liver X receptors (LXRs) were investigated. Molecular docking using crystal structures of the ligand binding domains (LBDs) of LXRα and β revealed high docking scores for L3 and D3 hydroxymetabolites, similar to those of the natural ligands, predicting good binding to the receptor. RNA sequencing of murine dermal fibroblasts stimulated with D3-hydroxyderivatives revealed LXR as the second nuclear receptor pathway for several D3-hydroxyderivatives, including 1,25(OH)2D3. This was validated by their induction of genes downstream of LXR. L3 and D3-derivatives activated an LXR-response element (LXRE)-driven reporter in CHO cells and human keratinocytes, and by enhanced expression of LXR target genes. L3 and D3 derivatives showed high affinity binding to the LBD of the LXRα and β in LanthaScreen TR-FRET LXRα and β coactivator assays. The majority of metabolites functioned as LXRα/β agonists; however, 1,20,25(OH)3D3, 1,25(OH)2D3, 1,20(OH)2D3 and 25(OH)D3 acted as inverse agonists of LXRα, but as agonists of LXRβ. Molecular dynamics simulations for the selected compounds, including 1,25(OH)2D3, 1,20(OH)2D3, 25(OH)D3, 20(OH)D3, 20(OH)L3 and 20,22(OH)2L3, showed different but overlapping interactions with LXRs. Identification of D3 and L3 derivatives as ligands for LXRs suggests a new mechanism of action for these compounds. | Accepted | https://pubmed.ncbi.nlm.nih.gov/33850196/ | April 13, 2021 | ||
| Linking Clinotypes to Phenotypes and Genotypes from Laboratory Test Results in Comprehensive Physical Exams. | BMC Medical Informatics and Decision Making | Thanh Nguyen, Tongbin Zhang, Geoffrey Fox, Sisi Zeng, Ni Cao, Chuandi Pan*, and Jake Y. Chen*. | In this work, we aimed to demonstrate how to utilize the lab test results and other clinical information to support precision medicine research and clinical decisions on complex diseases, with the support of electronic medical record facilities. We defined “clinotypes” as clinical information that could be observed and measured objectively using biomedical instruments. From well-known ‘omic’ problem definitions, we defined problems using clinotype information, including stratifying patients-identifying interested sub cohorts for future studies, mining significant associations between clinotypes and specific phenotypes-diseases, and discovering potential linkages between clinotype and genomic information. We solved these problems by integrating public omic databases and applying advanced machine learning and visual analytic techniques on two-year health exam records from a large population of healthy southern Chinese individuals (size n = 91,354). When developing the solution, we carefully addressed the missing information, imbalance and non-uniformed data annotation issues. | Vol. 21, Suppl 3: 51 doi.org /10.1186/s12911-021-01387-z. | Published | https://pubmed.ncbi.nlm.nih.gov/33627109/ | February 24, 2021 | |
| PAGER-CoV: A Comprehensive Collection of Pathways, Annotated-gene-lists, and Gene Signatures for Coronavirus Disease Studies | Nucleic Acids Research | Zongliang Yue, Eric Zhang, Clark Xu, Sunny Khurana, Nishant Batra, Son Dang, and Jake Y. Chen* | PAGER-CoV (http://discovery.informatics.uab.edu/PAGER-CoV/) is a new web-based database that can help biomedical researchers interpret coronavirus-related functional genomic study results in the context of curated knowledge of host viral infection, inflammatory response, organ damage, and tissue repair. The new database consists of 11 835 PAGs (Pathways, Annotated gene-lists, or Gene signatures) from 33 public data sources. Through the web user interface, users can search by a query gene or a query term and retrieve significantly matched PAGs with all the curated information. Users can navigate from a PAG of interest to other related PAGs through either shared PAG-to-PAG co-membership relationships or PAG-to-PAG regulatory relationships, totaling 19 996 993. Users can also retrieve enriched PAGs from an input list of COVID-19 functional study result genes, customize the search data sources, and export all results for subsequent offline data analysis. In a case study, we performed a gene set enrichment analysis (GSEA) of a COVID-19 RNA-seq data set from the Gene Expression Omnibus database. Compared with the results using the standard PAGER database, PAGER-CoV allows for more sensitive matching of known immune-related gene signatures. We expect PAGER-CoV to be invaluable for biomedical researchers to find molecular biology mechanisms and tailored therapeutics to treat COVID-19 patients. | IF = 11.5 | Published | https://pubmed.ncbi.nlm.nih.gov/33245774/ | January 8, 2021 | |
| Polar Gini Curve: a Quantitative Technique to Discover Gene Expression Spatial Patterns from Single-cell Data | Genomics, Proteomics, and Bioinformatics | Thanh Nguyen, Jacob Jeevan, Nuo Xu, and Jake Y. Chen | IF = 6.60 | Published | ||||
| Multi-omic Exploration of Inherent and Acquired Radiation Resistance of Glioblastoma Patient-derived Xenografts | International Journal of Radiation Oncology Biology Physics | C.D. Willey, C.T. Stackhouse, J.R. RowlandIII, C.P. Langford, J.C. Anderson, L. Ianov, Z. Yue, T. Nguyen, A.B. Hjelmeland, Jake Y. Chen, G.Y. Gillespie | Vol. 108, No. 3, Suppl., pp. S40 | Published | ||||
| Identifying the Key Regulators that Promote Cell-cycle Activity in the Hearts of Early Neonatal Pigs after Myocardial Injury | PLOS ONE | Eric Zhang, Thanh Nguyen, Meng Zhao, Son Do Hai Dang, Jake Y. Chen, Weihua Bian, and Gregory P Walcott | Mammalian cardiomyocytes exit the cell cycle shortly after birth. As a result, an occurrence of coronary occlusion-induced myocardial infarction often results in heart failure, postinfarction LV dilatation, or death, and represents one of the most significant public health morbidities worldwide. Interestingly however, the hearts of neonatal pigs have been shown to regenerate following an acute myocardial infarction (MI) occuring on postnatal day 1 (P1); a recovery period which is accompanied by an increased expression of markers for cell-cycle activity, and suggests that early postnatal myocardial regeneration may be driven in part by the MI-induced proliferation of pre-existing cardiomyocytes. In this study, we identified signaling pathways known to regulate the cell cycle, and determined of these, the pathways persistently upregulated in response to MI injury. We identified five pathways (mitogen associated protein kinase [MAPK], Hippo, cyclic [cAMP], Janus kinase/signal transducers and activators of transcription [JAK-STAT], and Ras) which were comprehensively upregulated in cardiac tissues collected on day 7 (P7) and/or P28 of the P1 injury hearts. Several of the initiating master regulators (e.g., CSF1/CSF1R, TGFB, and NPPA) and terminal effector molecules (e.g., ATF4, FOS, RELA/B, ITGB2, CCND1/2/3, PIM1, RAF1, MTOR, NKF1B) in these pathways were persistently upregulated at day 7 through day 28, suggesting there exists at least some degree of regenerative activity up to 4 weeks following MI at P1. Our observations provide a list of key regulators to be examined in future studies targeting cell-cycle activity as an avenue for myocardial regeneration. | Published | https://pubmed.ncbi.nlm.nih.gov/32730272/ | July 30, 2020 | ||
| Decoding SARS-CoV-2 Hijacking of Host Mitochondria in Pathogenesis of COVID-19 | American Journal of Physiology-Cell Physiology | Keshav K Singh, Gyneshwer Chaubey, Jake Y. Chen, and Prashanth Suravajhala. | Because of the ongoing pandemic around the world, the mechanisms underlying the SARS-CoV-2-induced COVID-19 are subject to intense investigation. Based on available data for the SARS-CoV-1 virus, we suggest how CoV-2 localization of RNA transcripts in mitochondria hijacks the host cell’s mitochondrial function to viral advantage. Besides viral RNA transcripts, RNA also localizes to mitochondria. SARS-CoV-2 may manipulate mitochondrial function indirectly, first by ACE2 regulation of mitochondrial function, and once it enters the host cell, open-reading frames (ORFs) such as ORF-9b can directly manipulate mitochondrial function to evade host cell immunity and facilitate virus replication and COVID-19 disease. Manipulations of host mitochondria by viral ORFs can release mitochondrial DNA (mtDNA) in the cytoplasm and activate mtDNA-induced inflammasome and suppress innate and adaptive immunity. We argue that a decline in ACE2 function in aged individuals, coupled with the age-associated decline in mitochondrial functions resulting in chronic metabolic disorders like diabetes or cancer, may make the host more vulnerable to infection and health complications to mortality. These observations suggest that distinct localization of viral RNA and proteins in mitochondria must play essential roles in SARS-CoV-2 pathogenesis. Understanding the mechanisms underlying virus communication with host mitochondria may provide critical insights into COVID-19 pathologies. An investigation into the SARS-CoV-2 hijacking of mitochondria should lead to novel approaches to prevent and treat COVID-19. | Vol. 319, No. 2 | Published | https://pubmed.ncbi.nlm.nih.gov/32510973/ | August 1, 2020 | |
| IL-23 promotes a coordinated B-cell germinal center program for class-switch recombination to IgG2b in BXD2 mice | J. Immunology, | Huixian Hong, Min Gao, Qi Wu, PingAr Yang, Shanrun Liu, Hao Li, Peter D. Burrows, Daniel Cua, Jake Y. Chen, Hui-Chen Hsu, and John D. Mountz | IL-23 promotes autoimmune disease, including Th17 CD4 T cell development and autoantibody production. In this study, we show that a deficiency of the p19 component of IL-23 in the autoimmune BXD2 (BXD2-p19-/- ) mouse leads to a shift of the follicular T helper cell program from follicular T helper (Tfh)-IL-17 to Tfh-IFN-γ. Although the germinal center (GC) size and the number of GC B cells remained the same, BXD2-p19-/- mice exhibited a lower class-switch recombination (CSR) in the GC B cells, leading to lower serum levels of IgG2b. Single-cell transcriptomics analysis of GC B cells revealed that whereas Ifngr1, Il21r, and Il4r genes exhibited a synchronized expression pattern with Cxcr5 and plasma cell program genes, Il17ra exhibited a synchronized expression pattern with Cxcr4 and GC program genes. Downregulation of Ighg2b in BXD2-p19-/- GC B cells was associated with decreased expression of CSR-related novel base excision repair genes that were otherwise predominantly expressed by Il17ra + GC B cells in BXD2 mice. Together, these results suggest that although IL-23 is dispensable for GC formation, it is essential to promote a population of Tfh-IL-17 cells. IL-23 acts indirectly on Il17ra + GC B cells to facilitate CSR-related base excision repair genes during the dark zone phase of GC B cell development. | Vol. 205(2), pp 346-358. (IF = 4.34) | Published | https://pubmed.ncbi.nlm.nih.gov/32554431/ | July 15, 2020 | |
| Guest Editorial for Selected Papers from BIOKDD 2018 and DMBIH 2018 | IEEE/ACM Transactions on Computational Biology and Bioinformatics | Da Yan, Xin Gao, Samah J. Fodeh, and Jake Y. Chen* | ol. 17, No. 6, pp. 1832-1834. | Published | ||||
| Polyvalent Therapeutic Vaccine for Type 2 Diabetes Mellitus: Immunoinformatics Approach to Study Co-Stimulation of Cytokines and GLUT1 Receptors | BMC Molecular and Cell Biology | Syed A Muhammad, Hiba Ashfaq, Sidra Zafar, Fahad Munir, Muhammad B Jamshed, Jake Y. Chen, and Qiyu Zhang | Type 2 diabetes mellitus (T2DM) is a worldwide disease that have an impact on individuals of all ages causing micro and macro vascular impairments due to hyperglycemic internal environment. For ultimate treatment to cure T2DM, association of diabetes with immune components provides a strong basis for immunotherapies and vaccines developments that could stimulate the immune cells to minimize the insulin resistance and initiate gluconeogenesis through an insulin independent route. | Vol. 21(1):56. doi: 10.1186/s12860-020-00279-w. (IF = 3.74) | Published | https://pubmed.ncbi.nlm.nih.gov/32703184/ | July 23, 2020 | |
| Association of CMV genomic mutations with symptomatic infection and hearing loss in congenital CMV infection | BMC Infectious Disease | George Dobbins, Amit Patki, Dongquan Chen, Hemant K. Tiwari, Curtis Hendrickson, William J. Britt, Karen Fowler, Jake Y. Chen, Suresh B Boppana, and Shannon A Ross* | Congenital cytomegalovirus (cCMV) infection is the most common congenital infection and a leading cause of long-term neurological and sensory sequelae, the most common being sensorineural hearing loss (SNHL). Despite extensive research, clinical or laboratory markers to identify CMV infected children with increased risk for disease have not been identified. This study utilizes viral whole-genome next generation-sequencing (NGS) of specimens from congenitally infected infants to explore viral diversity and specific viral variants that may be associated with symptomatic infection and SNHL. | Vol. 19(1);1046. doi: 10.1186/s12879-019-4681-0. (IF=2.58) | Published | https://pubmed.ncbi.nlm.nih.gov/31822287/ | December 10, 2019 | |
| WIPER: Weighted in-Path Edge Ranking for Biomolecular Association Networks | Quantitative Biology | Zongliang Yue, Thanh Nguyen, Eric Zhang, Jianyi Zhang, and Jake Y. Chen*. | In network biology researchers generate biomolecular networks with candidate genes or proteins experimentally-derived from high-throughput data and known biomolecular associations. Current bioinformatics research focuses on characterizing candidate genes/proteins, or nodes, with network characteristics, e.g., betweenness centrality. However, there have been few research reports to characterize and prioritize biomolecular associations (“edges”), which can represent gene regulatory events essential to biological processes. | Vol. 7, pp 313-326. | Published | https://link.springer.com/content/pdf/10.1007/s40484-019-0180-y.pdf | August 2, 2019 | |
| BEERE: a Web Server for Biomedical Entity Expansion, Ranking, and Explorations. Nucleic Acids Research, gkz428 (IF = 11.6) | Nucleic Acids Research | Zongliang Yue, Christopher D Willey, Anita B Hjelmeland, and Jake Y. Chen* | BEERE (Biomedical Entity Expansion, Ranking and Explorations) is a new web-based data analysis tool to help biomedical researchers characterize any input list of genes/proteins, biomedical terms or their combinations, i.e. ‘biomedical entities’, in the context of existing literature. Specifically, BEERE first aims to help users examine the credibility of known entity-to-entity associative or semantic relationships supported by database or literature references from the user input of a gene/term list. Then, it will help users uncover the relative importance of each entity-a gene or a term-within the user input by computing the ranking scores of all entities. At last, it will help users hypothesize new gene functions or genotype-phenotype associations by an interactive visual interface of constructed global entity relationship network. The output from BEERE includes: a list of the original entities matched with known relationships in databases; any expanded entities that may be generated from the analysis; the ranks and ranking scores reported with statistical significance for each entity; and an interactive graphical display of the gene or term network within data provenance annotations that link to external data sources. The web server is free and open to all users with no login requirement and can be accessed at http://discovery.informatics.uab.edu/beere/. | IF = 11.6 | Published | https://pubmed.ncbi.nlm.nih.gov/31114876/ | January 20, 2019 | |
| A GVHD-free Antitumoral Signature Following Allogeneic Donor Lymphocyte Injection Identified by Proteomics and Systems Biology | Biology. JCO Precision Oncology | Xiaowen Liu, Zongliang Yue, Yimou Cao, Lauren Taylor, Qing Zhang, Sung Wong Choi, Samir Hanash, Sawa Ito, Jake Y. Chen, Huanmei Wu, and Sophie Paczesny | As a tumor immunotherapy, allogeneic hematopoietic cell transplantation with subsequent donor lymphocyte injection (DLI) aims to induce the graft-versus-tumor (GVT) effect but often also leads to acute graft-versus-host disease (GVHD). Plasma tests that can predict the likelihood of GVT without GVHD are still needed. | Vol. 3, pp 1-11. | Published | https://pubmed.ncbi.nlm.nih.gov/31406955/ | May 23, 2019 | |
| Gsslasso Cox: a Bayesian hierarchical model for predicting survival and detecting associated genes by incorporating pathway information | BMC Bioinformatics | Zaixiang Tang, Shufeng Lei, Xinyan Zhang, Zixuan Yi, Boyi Guo, Jake Y. Chen, Yueping Shen, and Nengjun Yi | Group structures among genes encoded in functional relationships or biological pathways are valuable and unique features in large-scale molecular data for survival analysis. However, most of previous approaches for molecular data analysis ignore such group structures. It is desirable to develop powerful analytic methods for incorporating valuable pathway information for predicting disease survival outcomes and detecting associated genes. | Vol. 20, p. 94 | Published | https://pubmed.ncbi.nlm.nih.gov/30813883/ | February 27, 2019 | |
| Scalable De Novo Genome Assembly Using a Pregel-Like Graph-Parallel System. ACM/IEEE Transactions on Computational Biology and Bioinformatics, doi.org/10.1109/TCBB.2019.2920912 (IF = 1.96) | ACM/IEEE Transactions on Computational Biology and Bioinformatics, | Guimu Guo, Hongzhi Chen, Da Yan, James Cheng, and Jake Y. Chen | De novo genome assembly is the process of stitching short DNA sequences to generate longer DNA sequences, without using any reference sequence for alignment. It enables high-throughput genome sequencing and thus accelerates the discovery of new genomes. In this paper, we present a toolkit, called PPA-assembler, for de novo genome assembly in a distributed setting. The operations in our toolkit provide strong performance guarantees, and can be assembled to implement various sequencing strategies. PPA-assembler adopts the popular de Bruijn graph based approach for sequencing, and each operation is implemented as a program in Google’s Pregel framework which can be easily deployed in a generic cluster. Experiments on large real and simulated datasets demonstrate that PPA-assembler is much more efficient than the state-of-the-arts while providing comparable sequencing quality. PPA-assembler has been open-sourced at https://github.com/yaobaiwei/PPA-Assembler. | IF = 1.96 | Published | https://pubmed.ncbi.nlm.nih.gov/31180898/ | April 6, 2021 | |
| A Systematic Simulation-based Meta-analytical Framework for Prediction of Physiological Biomarkers in Alopecia | Journal of Biological Research-Thessaloniki | Syed Aun Muhammad*, Nighat Fatima, Rehan Zafar Paracha, Amjad Ali, and Jake Y. Chen* | Alopecia or hair loss is a complex polygenetic and psychologically devastating disease affecting millions of men and women globally. Since the gene annotation and environmental knowledge is limited for alopecia, a systematic analysis for the identification of candidate biomarkers is required that could provide potential therapeutic targets for hair loss therapy. | Vol. 26, No. 2 | Published | https://pubmed.ncbi.nlm.nih.gov/30993080/ | April 4, 2019 | |
| Multiscale and Multimodal Analysis for Computational Biology | IEEE/ACM Transactions on Computational Biology and Bioinformatics | Xin Gao, Jake Y. Chen, and Mohammed J. Zaki | Vol. 15, No. 6, pp. 1951-1952 (IF = 1.96) | Published | January 20, 2018 | |||
| Super Gene Set” Causal Relationship Discovery from Functional Genomics Data. ACM/IEEE Transactions on Computational Biology and Bioinformatics, Vol. 15, No. 6, pp. 1991-1998. (IF = 1.96) | ACM/IEEE Transactions on Computational Biology and Bioinformatics | Zongliang Yue, Michael T. Neylon, Thanh Nguyen, Timothy Ratliff, Jake Y. Chen* | In this article, we present a computational framework to identify “causal relationships” among super gene sets. For “causal relationships,” we refer to both stimulatory and inhibitory regulatory relationships, regardless of through direct or indirect mechanisms. For super gene sets, we refer to “pathways, annotated lists, and gene signatures,” or PAGs. To identify causal relationships among PAGs, we extend the previous work on identifying PAG-to-PAG regulatory relationships by further requiring them to be significantly enriched with gene-to-gene co-expression pairs across the two PAGs involved. This is achieved by developing a quantitative metric based on PAG-to-PAG Co-expressions (PPC), which we use to infer the likelihood that PAG-to-PAG relationships under examination are causal-either stimulatory or inhibitory. Since true causal relationships are unknown, we approximate the overall performance of inferring causal relationships with the performance of recalling known r-type PAG-to-PAG relationships from causal PAG-to-PAG inference, using a functional genomics benchmark dataset from the GEO database. We report the area-under-curve (AUC) performance for both precision and recall being 0.81. By applying our framework to a myeloid-derived suppressor cells (MDSC) dataset, we further demonstrate that this framework is effective in helping build multi-scale biomolecular systems models with new insights on regulatory and causal links for downstream biological interpretations. | Vol. 15, No. 6, pp | Published | https://pubmed.ncbi.nlm.nih.gov/30040650/ | July 23, 2018 | |
| Regenerative Potential of Neonatal Porcine Hearts | Circulation | Wuqiang Zhu, Eric Zhang, Meng Zhao, Zechen Chong, Chengming Fan, Yawen Tang, Jervaughn D. Hunter, Anton V. Borovjagin, Greggory P. Walcott, Jake Y. Chen, Gangjian Qin, Jianyi Zhang | Rodent hearts can regenerate myocardium lost to apical resection or myocardial infarction for up to 7 days after birth, but whether a similar window for myocardial regeneration also exists in large mammals is unknown. | Vol. 138, No. 24, pp. 2809-2816. (IF = 18.88) | Published | https://pubmed.ncbi.nlm.nih.gov/30030418/ | December 11, 2018 | |
| Simulation Study of cDNA Dataset to Investigate Possible Association of Differentially Expressed Genes of Human THP1-Monocytic Cells in Cancer Progression Affected by Bacterial Shiga Toxins | Frontiers in Microbiology | Syed Aun Muhammad*, Jinlei Guo, Thanh Minh Nguyen, Xiaogang Wu, Baogang Bai, X Frank Yang, Jake Y. Chen* | Shiga toxin (Stxs) is a family of structurally and functionally related bacterial cytotoxins produced by Shigella dysenteriae serotype 1 and shigatoxigenic group of Escherichia coli that cause shigellosis and hemorrhagic colitis, respectively. Until recently, it has been thought that Stxs only inhibits the protein synthesis and induces expression to a limited number of genes in host cells, but recent data showed that Stxs can trigger several signaling pathways in mammalian cells and activate cell cycle and apoptosis. To explore the changes in gene expression induced by Stxs that have been shown in other systems to correlate with cancer progression, we performed the simulated analysis of cDNA dataset and found differentially expressed genes (DEGs) of human THP1-monocytic cells treated with Stxs. In this study, the entire data (treated and untreated replicates) was analyzed by statistical algorithms implemented in Bioconductor packages. The output data was validated by the k-fold cross technique using generalized linear Gaussian models. A total of 50 DEGs were identified. 7 genes including TSLP, IL6, GBP1, CD274, TNFSF13B, OASL, and PNPLA3 were considerably (<0.00005) related to cancer proliferation. The functional enrichment analysis showed 6 down-regulated and 1 up-regulated genes. Among these DEGs, IL6 was associated with several cancers, especially with leukemia, lymphoma, lungs, liver and breast cancers. The predicted regulatory motifs of these genes include conserved RELA, STATI, IRFI, NF-kappaB, PEND, HLF, REL, CEBPA, DI_2, and NFKB1 transcription factor binding sites (TFBS) involved in the complex biological functions. Thus, our findings suggest that Stxs has the potential as a valuable tool for better understanding of treatment strategies for several cancers. | Vol. 9, No. 380 | Published | https://pubmed.ncbi.nlm.nih.gov/29593668/ | March 13, 2018 | |
| PAGER 2.0: An Update to the Pathway, Annotated-list, and Gene-signature Electronic Repository for Network Biology, | Nucleic Acids Research | Zongliang Yue, Qi Zheng, Micheal T Neylon, Minjae Yoo, Jimin Shin, Zhiying Zhao, Aik Choon Tan, and Jake Y. Chen | Integrative Gene-set, Network and Pathway Analysis (GNPA) is a powerful data analysis approach developed to help interpret high-throughput omics data. In PAGER 1.0, we demonstrated that researchers can gain unbiased and reproducible biological insights with the introduction of PAGs (Pathways, Annotated-lists and Gene-signatures) as the basic data representation elements. In PAGER 2.0, we improve the utility of integrative GNPA by significantly expanding the coverage of PAGs and PAG-to-PAG relationships in the database, defining a new metric to quantify PAG data qualities, and developing new software features to simplify online integrative GNPA. Specifically, we included 84 282 PAGs spanning 24 different data sources that cover human diseases, published gene-expression signatures, drug-gene, miRNA-gene interactions, pathways and tissue-specific gene expressions. We introduced a new normalized Cohesion Coefficient (nCoCo) score to assess the biological relevance of genes inside a PAG, and RP-score to rank genes and assign gene-specific weights inside a PAG. The companion web interface contains numerous features to help users query and navigate the database content. The database content can be freely downloaded and is compatible with third-party Gene Set Enrichment Analysis tools. We expect PAGER 2.0 to become a major resource in integrative GNPA. PAGER 2.0 is available at http://discovery.informatics.uab.edu/PAGER/. | Vol. 46, No. D1, pp. D668-D676. (IF = 10.0) | Published | https://pubmed.ncbi.nlm.nih.gov/29126216/ | January 4, 2018 | |
| Repositioning Drugs by Targeting Network Modules: A Parkinson’s Disease Case Study | BMC Bioinformatics | Zongliang Yue, Itika Arora, Eric Zhang, Vincent Laufer, S. Louis Bridges, and Jake Y. Chen* | Vol. 18, Suppl 14, 532. (IF = 2.75) | Published | https://pubmed.ncbi.nlm.nih.gov/29297292/ | December 28, 2017 | ||
| Characterization and Analysis of Long Non-Coding RNA (lncRNA) in in vitro- and ex vivo-derived Cardiac Progenitor Cells | PLOS ONE | Baron Arnone, Jake Y. Chen, and Gangjian Qin | Recent advancements in cell-based therapies for the treatment of cardiovascular disease (CVD) show continuing promise for the use of transplanted stem and cardiac progenitor cells (CPCs) to promote cardiac restitution. However, a detailed understanding of the molecular mechanisms that control the development of these cells remains incomplete and is critical for optimizing their use in such therapy. Long non-coding (lnc) RNA has recently emerged as a crucial class of regulatory molecules involved in directing a variety of critical biological processes including development, homeostasis and disease. As such, a rising body of evidence suggests that they also play key regulatory roles in CPC development, though many questions remain regarding the expression landscape and specific identity of lncRNA involved in this process. To address this, we performed whole transcriptome sequencing of two murine CPC populations-Nkx2-5 EmGFP reporter-sorted embryonic stem (ES) cell-derived and ex vivo, cardiosphere-derived-in an effort to characterize their lncRNA profiles and potentially identify novel CPC regulators. The resulting sequencing data revealed an enrichment in both CPC populations for a panel of previously-identified lncRNA genes associated with cardiac differentiation. Additionally, a total of 1,678 differentially expressed and as-of-yet unannotated, putative lncRNA genes were found to be enriched for in the two CPC populations relative to undifferentiated ES cells. | Vol. 12, No. 6, e0180096. (IF = 3.53) | Published | https://pubmed.ncbi.nlm.nih.gov/28640894/ | June 22, 2017 | |
| Integrative Approaches to Understanding the Pathogenic Role of Genetic Variation in Rheumatic Diseases | Rheumatic Disease Clinics | Vincent A. Laufer, Jake Y. Chen, S Louis Bridges Jr | The use of high-throughput omics may help to understand the contribution of genetic variants to the pathogenesis of rheumatic diseases. We discuss the concept of missing heritability: that genetic variants do not explain the heritability of rheumatoid arthritis and related rheumatologic conditions. In addition to an overview of how integrative data analysis can lead to novel insights into mechanisms of rheumatic diseases, we describe statistical approaches to prioritizing genetic variants for future functional analyses. We illustrate how analyses of large datasets provide hope for improved approaches to the diagnosis, treatment, and prevention of rheumatic diseases. | Vol. 43, No. 3, pp. 449-466. (IF = 1.98) | Published | https://pubmed.ncbi.nlm.nih.gov/28711145/ | August 4, 2017 |
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